Predicting drug release from polymer-based delivery systems remains challenging because release behavior depends on nonlinear interactions among formulation composition, polymer properties, drug characteristics, processing conditions, and time. This study develops an interpretable artificial intelligence framework for...
Mohammed Y. Ghazwani, Yahia Alghazwani, Umme Hani· Frontiers in Medicine· 0 citations
The optimized Artemether-loaded nanoemulsion developed using a Box–Behnken Design significantly enhanced the drug’s dissolution and exhibited favorable physicochemical characteristics, high entrapment efficiency, and controlled release behavior, suggesting that nanoemulsion is a promising carrier system warranting furt...
The correct time-course forecasting of the release of a drug contained in a drug-polymer matrix is difficult because drug dissolution is a complex process involving all formulation parameters, which are interdependent and have nonlinear effects. Although the predictive accuracy of machine learning (ML) models is high,...
Mohammed Y. Ghazwani, Yahia Alghazwani, Umme Hani· Frontiers in Medicine· 0 citations
Overall, the moderate promising leads of NT1 and NT9 emerged with dual-target potential for breast cancer, supporting further optimization and preclinical assessment.
C. N. Babu, Mazin Aboobaida Abdalla Abdelaziz, N. Nizamuddin et al.· Journal of Pharmaceutical In...· 0 citations
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